Price Your Cardmarket Inventory With TCG Powertools (Full Tutorial)

Summary

This video is a practical tutorial on using TCG Power Tools to price trading-card inventory on Cardmarket. The presenter’s core advice is to benchmark against sellers customers are likely to consider, reprice inventory regularly, and keep pricing rules simple enough to manage.

Pricing workflow and playbook

• Set minimum prices first. Minimum prices act as hard floors: if a pricing rule calculates a lower price, the floor is used instead. Floors can be configured separately by game, card type, or rarity.
  • The presenter’s Magic examples are €0.05 for regular cards, €0.07 for uncommons, €0.12 for rares, and €0.15 for masterpieces and special cards.
  • Minimum prices can also help control order volume. The presenter says very low floors can generate more low-value and wholesale sales, while floors above €0.10 may slow sales unless inventory is very large.
• Define relevant competitors. Build competitor groups using filters such as marketplace, seller type, country, reputation, sales history, and excluded sellers.
  • The presenter’s example targets professional or power sellers in Germany with an “outstanding” rating and at least 1,000 sales.
  • Country selection matters because local demand, shipping costs, language, and buyer preferences affect which listings are genuine alternatives.
  • Filtering out lower-reputation or less-established sellers can raise the benchmark price. In the example, a card listed at €0.09 in France had a lowest qualifying German professional-seller offer of €0.90.
• Choose a pricing basis.
  • Competition-based: Price relative to a selected competitor group and offer position, such as the third- or ninth-cheapest listing.
  • Price-guide-based: Price as a percentage of Cardmarket trend or average metrics, including its 1-day, 7-day, and 30-day averages.
  • Matching settings can account for card condition and language. The presenter recommends considering same-language and English listings, particularly for less common languages.
• Use modifiers and floors deliberately. A strategy can price below or above a benchmark by a fixed amount or percentage. Minimum prices prevent an automated rule from taking a card below its floor.
• Consider a min-max strategy. Run two pricing calculations and select the higher or lower result.
  • For example, 80% of the third-cheapest offer gives about €0.77, while 80% of a €1.14 price trend gives about €0.91. A maximum-price rule selects €0.91, avoiding an excessively low price.
• Apply rules to inventory in bulk. Filter inventory by game, rarity, or other attributes, select cards, and run automatic pricing. Individual cards can also be inspected for current offers and trend data before adjusting them.

Repricing operations and controls

• Use the pricing bot for recurring updates. A static price list can become misaligned as individual card values move: some cards may sell too cheaply, while overpriced cards stop selling. The bot can recalculate prices nightly.
• Set boundaries and review results. Bot settings can include maximum percentage increases or decreases, maximum price increases, and a minimum change threshold. The presenter uses a 0.1% minimum change threshold in the example and demonstrates reviewing which cards changed.
• Use ordered rules carefully. Rules are processed in sequence: cards matched by an earlier rule are removed from the pool for later rules. Put more specific groups first—for example, mythics before a broader rare-or-higher rule—to prevent cards from being handled by the wrong rule.
• Combine filters with AND conditions. For example, a rule can apply only to cards that are both mythic and priced between €1 and €1,000. OR conditions can represent separate rule groups.
• Protect manual prices with a comment convention. The presenter uses “NP” in a card comment to mean “no pricing/no bot.” This keeps manually priced or specially discounted cards from being overwritten by automated repricing.

Concrete operating examples and guidance

• The presenter’s simplified Magic strategy is to price €0.01 below the third-cheapest offer from professional German sellers. Cards marked NP are excluded from bot repricing.
• Manually review scarce or expensive cards. Automated position-based rules can behave poorly when there are only a few listings—for example, when a few reasonably priced offers are followed by extreme, unrealistic prices. The presenter recommends checking such cards individually and excluding them from the bot if necessary.
• Tailor competitor filters to the customer base. A seller in a large domestic market may primarily compete locally, while sellers in smaller countries may rely more on cross-border orders. Buyers in those cases may place larger orders to justify shipping, making a broad assortment and slightly higher prices more viable.
• Avoid unnecessary complexity. The presenter recommends starting with a small set of workable strategies instead of creating separate rules for every rarity, foil, or token. Track whether the chosen floor and competitive position produce consistent sales, then adjust as needed.

Metrics and scale mentioned

• The presenter’s inventory dashboard shows approximately 15,000 unique items and 25,000 units. Later examples refer to 13,000 Magic items and nearly 8,000 cards in a bulk-pricing scenario.
• Bot testing is described as covering about 1,000 items, while a nightly recalculation affects about 10,000 items. Very large inventories may therefore take multiple days to cycle through because of technical and API constraints.
• A bot report example shows a group of repriced cards moving in total from €199.57 to €196.53. An individual example changes from €0.84 to €0.49. These illustrate repricing outcomes, not performance targets.

Presenter: SGB Cards host; the host’s name is unclear in the subtitles. Sources and platforms discussed: TCG Power Tools and Cardmarket.